Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output. The high variability of this renewable energy source can caused a disruptive effect on power quality and reliability, in non-interconnected island networks as in Guadeloupe (French West Indies). To palliate these difficulties, it is essential to identify and characterize the wind speed distribution over very short time intervals. This allows anticipating the eventuality of power shortage or power surge. Therefore, it is of interest to categorize wind speed fluctuations into distinct classes and to estimate the probability of a distribution to belong to a class. This paper presents a method for classifying wind speed distributions by estimating a finite mixture of Dirichlet distributions. The SAEM algorithm that we use provides a fine distinction between three wind speed distribution classes. It is a new nonparametric method for wind speed classification.
ISSN: 0960-1481

hal-01527881
https://hal.archives-ouvertes.fr/hal-01527881
DOI : 10.1016/j.renene.2011.03.024

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Wind energy production is very sensitive to turbulent wind speed. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output, in particular when wind power variations on very short time scales, range at few seconds to 1 h, are considered. In small grid as they exist on islands (Guadeloupean Archipelago: French West Indies) such fluctuations can cause instabilities in case of intermediate power shortages. The developed analysis in [14] reveals three main classes of time series for the wind speed fluctuations. In this work, Probability Density Functions (PDFs) are proposed to fit the wind speed fluctuations distributions in each class. After, to simulate wind speed fluctuations sequences, we use a stochastic differential equation, the Langevin equation considering Gaussian turbulence PDF (class I), Gram–Charlier PDF (class II) and a mixture of gaussian PDF (class III). The statistical and dynamical properties of simulated wind sequences are close to those of measured wind sequences, for each class
ISSN: 0306-2619

hal-01527885
https://hal.archives-ouvertes.fr/hal-01527885
DOI : 10.1016/j.apenergy.2012.05.007

Éditeur(s) : Wiley-Blackwell
Résumé : The Climate Forecast System Reanalysis (CFSR) provides a wealth of information spanning 1979–2009 for investigation of ocean wind and wave climate. Preprocessing of the data is necessary to remove the dominant seasonal signals and to create time series of semimonthly averaged wind speed and significant wave height over a 0.5° global grid. We perform an empirical orthogonal function (EOF) analysis to extract the dominant space-time patterns. The results for the three major ocean basins show strong zonal structures in the winds and saturation of the swells corroborating prior works with various data sets. We reexamine the CFSR data in the frequency domain to identify periodic signals associated with published climate indices. The Fourier transform of the preprocessed time series generates spectra ranging from 1 month to 15 years period for an EOF analysis. The results demonstrate the spatial structures and periods of climate phenomena. The Arctic Oscillation dominates the Atlantic basin with a broad range of intra-annual signals off the European coasts. The Indian and Pacific Oceans are strongly influenced by inter-annual cycles of the El Niño Southern Oscillation (ENSO) and the Antarctica Oscillation. The Indian Ocean also has strong intra-annual components ranging from 50 to 80 days period. The ENSO proves to be a ubiquitous signal around the globe, and in particular, saturates the Pacific with strong influences in the equatorial region and the Southern Hemisphere Westerlies. A commonality of all basins is that the magnitude and the spatial structure of the intra-annual and inter-annual signals are similar suggesting a wide range of periods in each of the climate cycles examined.
Journal of Geophysical Research: Oceans (21699275) (Wiley-Blackwell), 2014-08 , Vol. 119 , N. 8 , P. 5563-5584

Droits : 2014. American Geophysical Union. All Rights Reserved.
http://archimer.ifremer.fr/doc/00210/32149/30606.pdf
http://archimer.ifremer.fr/doc/00210/32149/30607.pdf
DOI:10.1002/2013JC009729
http://archimer.ifremer.fr/doc/00210/32149/

Éditeur(s) : HAL CCSD
Résumé : 20 pp
We first analyze some atmospheric parameters measured in 2004 at the top of La Soufrière volcano: wind speed, pressure and temperature. Next, we study the stochastic process of the wind speed modulus which is of interest for prediction of pollution induced by the plume. We fit to the data various models : FARIMA, periodic trend plus multifractional Brownian noise, multifractal continuous cascades. The estimations show that they evoluate during some transition phases in response to environment changes. Thus, we finally suggest, for future works, some settings that should be more appropriate: time series with regime changes and stochastic processes in random environment.
https://hal.archives-ouvertes.fr/hal-00165572

hal-00165572
https://hal.archives-ouvertes.fr/hal-00165572
https://hal.archives-ouvertes.fr/hal-00165572/document
https://hal.archives-ouvertes.fr/hal-00165572/file/Windsouf_v11.pdf

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
Wind energy production is very sensitive to turbulent wind, in particular when wind power variations range from few seconds to 1 hour, are considered. Indeed rapid changes in the local meteorological condition as observed in tropical climate can provoke large variations of wind speed. Consequently the electric grid security can be jeopardized due to these fluctuations. This is particularly the case of island networks as in the Guadeloupean archipelago (French West Indies) where the installed 20 MW wind power already represents 11% of the electrical consumption. From 1 million wind sequences of duration 10 minutes, sampled at 1 Hz during the trade season, we proceed toward two objectives: i) the characterization of the wind speed sequences, ii) the dynamical simulation of the wind sequences using Langevin equation.
Progress in Turbulence and Wind Energy IV

ISBN : 978-3-642-28968-2.
hal-01527883
https://hal.archives-ouvertes.fr/hal-01527883
DOI : 10.1007/978-3-642-28968-2-50

Éditeur(s) : Ieee-inst Electrical Electronics Engineers Inc
Résumé : The synthetic aperture radar (SAR) Doppler centroid has been used to estimate the scatter line-of-sight radar velocity. In weak to moderate ocean surface current environment, the SAR Doppler centroid is dominated by the directionality and strength of wave-induced ocean surface displacements. In this paper, we show how this sea state signature can be used to improve surface wind retrieval from SAR. Doppler shifts of C-band radar return signals from the ocean are thoroughly investigated by colocating wind measurements from the ASCAT scatterometer with Doppler centroid anomalies retrieved from Envisat ASAR. An empirical geophysical model function (CDOP) is derived, predicting Doppler shifts at both VV and HH polarization as function of wind speed, radar incidence angle, and wind direction with respect to radar look direction. This function is used into a Bayesian inversion scheme in combination with wind from a priori forecast model and the normalized radar cross section (NRCS). The benefit of Doppler for SAR wind retrieval is shown in complex meteorological situations such as atmospheric fronts or low pressure systems. Using in situ information, validation reveals that this method helps to improve the wind direction retrieval. Uncertainty of the calibration of Doppler shift from Envisat ASAR hampers the inversion scheme in cases where NRCS and model wind are accurate and in close agreement. The method is however very promising with respect of future SAR missions, in particular Sentinel-1, where the Doppler centroid anomaly will be more robustly retrieved.
Ieee Transactions On Geoscience And Remote Sensing (0196-2892) (Ieee-inst Electrical Electronics Engineers Inc), 2012-07 , Vol. 50 , N. 7 , P. 2901-2909

Droits : 2012 IEEE
http://archimer.ifremer.fr/doc/00088/19896/17554.pdf
DOI:10.1109/TGRS.2011.2174998
http://archimer.ifremer.fr/doc/00088/19896/

Éditeur(s) : HAL CCSD Geological Society of America
Résumé : International audience
Lakes are major depositional systems for which the related depositional processes have long been considered relatively simple. Breaking this statement, this study presents a detailed analysis of deposits in Lake Saint-Jean, the third largest natural lake in Québec. In addition to postglacial deltaic and coastal depositional systems fringing the lake, current-controlled features such as a large subaqueous prograding wedge and three sediment drifts have been identifi ed in its central portion based on two-dimensional (2-D) acoustic high-resolution subbottom profiles. The large subaqueous prograding wedge is a 4-km-long and up to 15-m-thick heterolithic shelf-like construction in the southeastern part of the lake. The three sediment drifts are 0.1–0.5-km-long and 2–5-mthick mud mounds distributed on the lake floor in the central portion of the lake. Diatom analyses and radiocarbon dating show that the development of these current-controlled features occurred during the lacustrine phase, after the disconnection with the postglacial marine Laflamme Gulf at 8.5 cal. k.y. B.P. Depositional facies show evidence of recurrent bottom-current activity. Related deposits alternate with pelagic sedimentation stages characterized by the settling of mud and biogenic accumulations. We investigated the origin of bottom currents using a numerical simulation (SYMPHONIE, an oceanographic model), with the aim of modeling wind-induced lake-scale water circulation. Simulations suggest that the subaqueous prograding wedge and the three sediment drifts result from wind-induced bottom currents generated by storm events having wind speed greater than 10 m s–1. Such strong winds are able to significantly affect sedimentation in the central portion of Lake Saint-Jean. Theresulting wind-induced sedimentary features were integrated into a refi ned lacustrine depositional model that summarizes the evolution of a group of water bodies referred to as “wind-driven water bodies.” This study applies a new tool for lake strata characterization and highlights the potential diffi cultyin differentiating them from marine deposits in the geological record.
ISSN: 0016-7606

insu-01184724
https://hal-insu.archives-ouvertes.fr/insu-01184724
DOI : 10.1130/B31145.1

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we have presented a spectral and a multifractal analysis performed on 412 time series of wind speed data each of duration of 350 s and sampled at 20 Hz. The average spectrum for the wind speed displays a scaling behavior, in the inertial range, over two decades, with b ¼ 1:68 close to the Kolmogorov value À 5/3. A multifractal analysis has been motivated by the presence of scaling invariance in data set. Then we have considered their scaling properties in the framework of fully developed turbulence and multifractal cascades. The results obtained for wind speed confirm that the exponent scaling function z V ðqÞ is nonlinear and concave. This exponent characterizes the scaling functions in the inertial range indicating that the wind speed is intermittent and multifractal. Moreover the theoretical quadratic relation for lognormal multifractals is well fitted. We investigate the consequence for wind energy production: we generate stochastic simulations of a multifractal random walk, and using a power curve derived from experimental data, we generate the associated power time series. We show that, due to the saturation of the power curve for large speed values, when the input time series (turbulent wind speed) is multifractal, the output can be almost monofractal.
ISSN: 0167-6105

hal-01527886
https://hal.archives-ouvertes.fr/hal-01527886
DOI : 10.1016/j.jweia.2012.06.002

Éditeur(s) : HAL CCSD European Geosciences Union (EGU)
Résumé : International audience
We consider here wind speed time series and the aggregate output wind power from a wind farm. We study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. We estimate their Fourier power spectra and consider their scaling properties in the physical space. We show that the atmospheric wind speed and the aggregate power output from a wind farm are intermittent and multifractal over a wide range of scales. The coupling between simultaneous data of the wind speed and aggregate power output is investigated through a joint multifractal description using the generalized correlation functions (GCFs). This multiscaling test is compatible with a linear relation between the wind speed and the aggregate power output fluctuations for timescales T ⩾ 103 s ≃ 15 min
ISSN: 1023-5809

hal-01527893
https://hal.archives-ouvertes.fr/hal-01527893
DOI : 10.5194/npg-21-379-2014

Éditeur(s) : HAL CCSD
Résumé : 32 pages
Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output. In small grids, as they exist for example on some islands in the French West Indies, such fluctuations can cause instabilities in case of intermediate power shortages. To palliate these difficulties, it is essential to identify and characterize the wind speed distributions. This allows to anticipate the eventuality of power shortage or power surge. Therefore, it is of interest to categorize wind speed fluctuations into distinct classes and to estimate the probability of a distribution to belong to a class. This paper presents a method for classifying wind speed histograms by estimating a finite mixture of Dirichlet distributions. The SAEM algorithm that we use provides a fine distinction between wind speed distribution classes. It's a new nonparametric method for wind speed sequences classification. However, we show that the wind speed distributions in each class correspond to specific Gram- Charlier densities.
https://hal.archives-ouvertes.fr/hal-00319608

hal-00319608
https://hal.archives-ouvertes.fr/hal-00319608
https://hal.archives-ouvertes.fr/hal-00319608v2/document
https://hal.archives-ouvertes.fr/hal-00319608/file/Article_dirichlet.pdf
ARXIV : 0810.4422

Éditeur(s) : HAL CCSD European Geosciences Union (EGU)
Résumé : International audience
We consider here wind speed time series and the aggregate output wind power from a wind farm. We study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. We estimate their Fourier power spectra and consider their scaling properties in the physical space. We show that the atmospheric wind speed and the aggregate power output from a wind farm are intermittent and multifractal over a wide range of scales. The coupling between simultaneous data of the wind speed and aggregate power output is investigated through a joint multifractal description using the generalized correlation functions (GCFs). This multiscaling test is compatible with a linear relation between the wind speed and the aggregate power output fluctuations for timescales T > 103 s ' 15min.
ISSN: 1023-5809

hal-00958490
https://hal.archives-ouvertes.fr/hal-00958490
DOI : 10.5194/npg-21-379-2014

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
Few studies have investigated the influence of environmental conditions on the within-treevariation in Eucalyptus wood traits. The genotype and environment effects and their interactionsinfluence the wood properties. Their evaluations are crucial to estimate the genotype values andto select with efficiency. Thus, the aim of this study was to better understand the effect ofground slope and wind speed on the spatial variation of basic density (ρ), stiffness (MOE) andmicrofibril angle (MFA) of Eucalyptus wood. Wood discs cut along the trunk were sampledfrom 150 six-year-old Eucalyptus grandis x E. urophylla hybrids growing in 3 contrastinggrowing conditions influenced by ground slope and wind regime. Near Infrared (NIR)calibrations previously developed for ρ, MOE and MFA were used to predict in our discs. 2-Dplots presenting the spatial variation of predicted wood traits were compared. The higher theground slope, the greater the magnitude of radial variation in ρ, principally in the medium zoneof the trunk. The spatial variation of wood stiffness seems to be sensitive to two environmentalconditions. The MFA radial decreases were more pronounced where the wind speed was higher.At the base and top of the trees, however, there was no significant effect of growing conditionson the radial variation of the wood properties considered here.
ISSN: 0931-1890

hal-01451896
https://hal.archives-ouvertes.fr/hal-01451896
https://hal.archives-ouvertes.fr/hal-01451896/document
https://hal.archives-ouvertes.fr/hal-01451896/file/Art_Gril_al_Spatial_variation_wood_density_2016.pdf
DOI : 10.1007/s00468-015-1327-8

Éditeur(s) : HAL CCSD Springer
Résumé : In this work, we present an analysis of one-year period measured wind speed in the atmospheric boundary layer from a wind energy production site. We employ a Hilbert-based methodology, namely arbitrary-order Hilbert spectral analysis to characterize the intermittent property of the wind speed in a joint amplitudefrequency space. The measured scaling exponents implies intermittent nature of the wind on mesoscales.
Wind Energy: Impact of Turbulence

ISBN : 978-3642546952
hal-00958512
https://hal.archives-ouvertes.fr/hal-00958512

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
We have measured simultaneously the methane (CH4) and carbon dioxide (CO2) surface concentrations and water–air fluxes by floating chambers (FC) in the Petit-Saut Reservoir (French Guiana) and its tidal river (Sinnamary River) downstream of the dam, during the two field experiments in wet (May 2003) and dry season (December 2003). The eddy covariance (EC) technique was also used for CO2 fluxes on the lake. The comparison of fluxes obtained by FC and EC showed little discrepancies mainly due to differences in measurements durations which resulted in different average wind speeds. When comparing the gas transfer velocity (k600) for a given wind speed, both methods gave similar results. On the lake and excluding rainy events, we obtained an exponential relationship between k600 and U10, with a significant intercept at 1.7 cm h− 1, probably due to thermal effects. Gas transfer velocity was also positively related to rainfall rates reaching 26.5 cm h−1 for a rainfall rate of 36 mm h− 1. During a 24-h experiment in dry season, rainfall accounted for as much as 25% of the k600. In the river downstream of the dam, k600 values were 3 to 4 times higher than on the lake, and followed a linear relationship with U10.
ISSN: 0924-7963

hal-00519502
https://hal.archives-ouvertes.fr/hal-00519502
DOI : 10.1016/j.jmarsys.2006.03.019

Éditeur(s) : HAL CCSD Intech
Résumé : International audience
The massive integration of sustainable energies into electrical grids (non-interconnectedor connected) is a major problem due to their stochastic character revealed by strongfluctuations at all scales. In this paper, the scaling behaviour or power law correlationsand the nature of scaling behaviour of sustainable resource data such as flow velocity,atmospheric wind speed, solar global solar radiation and sustainable energy such as,wind power output, are highlighted. For the first time, Fourier power spectral densitiesare estimated for each dataset. We show that the power spectrum densities obtained areclose to the 5/3 Kolmogorov spectrum. Furthermore, the multifractal and intermittentproperties of sustainable resource and energy data have been revealed by the concavityof the scaling exponent function. The proposed analysis frame allows a full descriptionof fluctuations of processes considered. A good knowledge of the dynamic of fluctua-tions is crucial to management of the integration of sustainable energies into a grid.
Sustainable Energy - Technological Issues, Applications and Case Studies

hal-01528087
https://hal.archives-ouvertes.fr/hal-01528087
DOI : 10.5772/106341

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we have presented a spectral and a multifractal analysis performed on 412 time series of wind speed data each of duration of 350 s and sampled at 20 Hz. The average spectrum for the wind speed displays a scaling behavior, in the inertial range, over two decades, with β=1.68 close to the Kolmogorov value −5/3. A multifractal analysis has been motivated by the presence of scaling invariance in data set. Then we have considered their scaling properties in the framework of fully developed turbulence and multifractal cascades. The results obtained for wind speed confirm that the exponent scaling function ζV(q) is nonlinear and concave. This exponent characterizes the scaling functions in the inertial range indicating that the wind speed is intermittent and multifractal. Moreover the theoretical quadratic relation for lognormal multifractals is well fitted. We investigate the consequence for wind energy production: we generate stochastic simulations of a multifractal random walk, and using a power curve derived from experimental data, we generate the associated power time series. We show that, due to the saturation of the power curve for large speed values, when the input time series (turbulent wind speed) is multifractal, the output can be almost monofractal.
ISSN: 0167-6105

hal-00779049
https://hal.archives-ouvertes.fr/hal-00779049
DOI : 10.1016/j.jweia.2012.06.002

Éditeur(s) : American Geophysical Union
Résumé : [1] Extreme weather events such as tropical cyclones are difficult to observe with conventional means. Satellite-based observations provide essential measurements of key parameters governing tropical cyclones. They are critical for short-term forecasting. Radiometers onboard the Defense Meteorological Satellite Program satellite series, WindSat and Tropical Rainfall Measuring Mission satellites, scatterometers onboard the ERS, ADEOS, and QuikScat satellites offer unprecedented synoptic observations of surface wind and atmospheric liquid water content, revealing the storm structures with good accuracy. However, satellite estimates do not provide direct measurements of geophysical parameters and can suffer from limitations linked to the sensors characteristics, such as the signal wavelength and polarization or the measurement incidence angle. For example, measurements at Ku band are strongly affected by rain. Still, each observing system can offer specific information that can be combined with the others. In particular, we highlight the capabilities of dual-frequency altimeter to provide very high resolution measurements of rain rate, surface wind speed, and wave characteristics. A method is proposed to obtain continuous along-track 5 km resolution measurements of these parameters in the tropical cyclone Isabel. The results shows that dual-frequency altimeters can provide useful information to complement and validate the operational fields provided by the atmospheric numerical models and by NOAA observing systems.
Journal of Geophysical Union - Research C - Oceans (0148-0227) (American Geophysical Union), 2006 , Vol. 111 , N. C1 , P. NIL_38-NIL_50

Droits : 2006 American Geophysical Union
http://archimer.ifremer.fr/doc/2006/publication-1033.pdf
DOI:10.1029/2005JC003068
http://archimer.ifremer.fr/doc/00000/1033/

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we present an analysis of a one-year period measured wind speed in the atmospheric boundary layer from a wind energy production site. We employ a Hilbert-based methodology, namely arbitrary-order Hilbert spectral analysis, to characterize the intermittent property of the wind speed in a joint amplitude-frequency space. The measured scaling exponents implies intermittent nature of the wind on mesoscales.
Wind Energy-Impact of turbulence

hal-01528079
https://hal.archives-ouvertes.fr/hal-01528079
DOI : 10.1007/978-3-642-54696-9

Éditeur(s) : HAL CCSD
Résumé : 15 pages
A Stochastic Differential Equation appearing in the statistical theory of turbulence is extended in random environment by assuming that its two parameters are switched by an unobserved continuoustime Markov chain whose states represent the states of the environment. A Dirichlet process is placed as a prior on the space of the sample paths of this chain, leading to a hierarchical Dirichlet model whose estimation is done both on simulated data and on real data of wind speed measured at the entrance of a mangrove ecosystem.
https://hal.archives-ouvertes.fr/hal-00455050

hal-00455050
https://hal.archives-ouvertes.fr/hal-00455050
https://hal.archives-ouvertes.fr/hal-00455050/document
https://hal.archives-ouvertes.fr/hal-00455050/file/CSDA06_Srik_Hal.pdf

Résumé : La forte variabilité de la vitesse du vent fait que l'énergie produite par un parc éolien n'est pas constante dans le temps. Le gestionnaire ne peut donc pas dimensionner son réseau électrique en prenant intégralement ce type de production en compte. L' une des solutions préconisées pour permettre le développement de l' éolien et son intégration avec une plus grande sureté aux réseaux, est de développer et d'améliorer les outils de prévisions. Le travail de thèse consiste à améliorer les performances d'un outil de prédiction basé sur les réseaux de neurones bayesiens, permettant la prédiction de la puissance à très court terme . Le prédicteur fonctionne notamment par J'ajustement de paramètres, certain se détermine « automatiquement » via le mécanisme des réseaux de neurones bayesiens d' autres, que nous nommerons paramètres temporels, sont à l' appréciation de l'utilisateur. Le travail mené consiste à établir un protocole pour la fixation de ces paramètres tout en améliorant les performances du prédicteur . Nous avons donc décidé de conditionner leurs valeurs en fonction de la variabilité des séquences de puissance précédent l'instant de prévision. Tout d'abord nous avons classifié des séquences de puissance en fonction de leurs coefficients de variation en appliquant la méthode des C-moyennes floues. Puis, chaque classe formée a été testée sur plusieurs valeurs de paramètres, les valeurs associées aux meilleures prédictions ont été retenues. Enfin, ces résultats couplés au formalisme des Chaines de Markov, par le biais de la matrice de transition , ont perm is d'obtenir des taux d'amélioration par rapport à la persistance allant de 7,73 à 23,22 % selon l'horizon de prédiction considéré
The high variability of the wind speed has for conse quences that the energy produced by a wind farm is not constant over time. Therefore, the manager can't size the electrical network by takin g into account this type of production. One solution advocated for the development of wind energy and its integrati on with greater security at network, is to develop and improve fore casting tools. The thesi s objective is to improve the performance of a predi ction tool based on Bayesian neural networks, allowing the predi ction of wind power for short timescales. The predictor works, in part icular by the adjustment of parameters, sorne is determined "automatically" through the mechan ism of neural networks Bayesian other , which we cali temporal parameters are at the discretion of the user. The work involves establishing a protocol for the determination of these parameters and improving the performance of the predictor. So, we decided to condition their values depending on the sequence variability of wind power previous the moment of the forecast. First we classified sequences of power according to their coefficients of variation using the method of fuzzy C-means. Then, each formed class was tested for several parameters values, the values associated with the best predictions were selected. Finally , these result s coupled with the formalism of Markov chains , through the transition matrix allowed to obtain rates of improvement over the persistence ranging from 7.73 to 23.22 % depending on the prediction horizon considered

http://www.theses.fr/2013AGUY0679/document